I'm using this code:
h1 <- glm(pol_violence ~ defense + gdp + polityold + instabilityold + personalist + military_dic , data = dataset) summary(h1) h2 <- glm(deliberal ~ defense + gdp + polityold + personalist , family = "binomial" , data = dataset) summary(h2)
But I get this:
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 2.457e+01 1.883e+05 0 1 defense1 -4.913e+01 2.441e+05 0 1 gdp 6.142e-10 8.637e+01 0 1 polityold 9.579e-09 1.523e+04 0 1 personalist1 6.938e-07 1.911e+05 0 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 7.6382e+00 on 5 degrees of freedom Residual deviance: 2.5720e-10 on 1 degrees of freedom (16 observations deleted due to missingness) AIC: 10 Number of Fisher Scoring iterations: 23
I dont understand why my model is unfit, or what I should do to fix the 0 in z value?
Help me please.
my dataset consists of 22 country observations with the years in which a military intervention occurred during a popular uprising. my hypotheses are H1: the stronger the military veto power during the uprising, the more likely there is political instability H2: the stronger the military veto power during the uprising, the more likely there is deliberalization
my independent variable military veto power is operationalized with the variable "defense" which expresses whether the defense minister is a military officer (then its coded as 1) if not, its coded 0.
my dependent variables are pol_violence which expresses instability. its coded 1 if there is political instability and 0 if there is non.
same goes to the other dependent variable deliberal which expresses deliberalization. 1 if there is deliberalization , 0 if there is non.
the other variables are control variables, 2 of them (personalist and military_dic) are binary and are coded 1 if there is a personalist leader or a military leader, 0 if non.
gdp is self explanatory. instabilityold expresses instability rate from the year before, the higher the number the more instability
polityold is the polity iv democracy rate from the year before, the higher the number the stronger the democracy.
the values 66 and 2 are missing variables